• NCERT Solutions
    • NCERT Library
  • RD Sharma
    • RD Sharma Class 12 Solutions
    • RD Sharma Class 11 Solutions Free PDF Download
    • RD Sharma Class 10 Solutions
    • RD Sharma Class 9 Solutions
    • RD Sharma Class 8 Solutions
    • RD Sharma Class 7 Solutions
    • RD Sharma Class 6 Solutions
  • Class 12
    • Class 12 Science
      • NCERT Solutions for Class 12 Maths
      • NCERT Solutions for Class 12 Physics
      • NCERT Solutions for Class 12 Chemistry
      • NCERT Solutions for Class 12 Biology
      • NCERT Solutions for Class 12 Economics
      • NCERT Solutions for Class 12 Computer Science (Python)
      • NCERT Solutions for Class 12 Computer Science (C++)
      • NCERT Solutions for Class 12 English
      • NCERT Solutions for Class 12 Hindi
    • Class 12 Commerce
      • NCERT Solutions for Class 12 Maths
      • NCERT Solutions for Class 12 Business Studies
      • NCERT Solutions for Class 12 Accountancy
      • NCERT Solutions for Class 12 Micro Economics
      • NCERT Solutions for Class 12 Macro Economics
      • NCERT Solutions for Class 12 Entrepreneurship
    • Class 12 Humanities
      • NCERT Solutions for Class 12 History
      • NCERT Solutions for Class 12 Political Science
      • NCERT Solutions for Class 12 Economics
      • NCERT Solutions for Class 12 Sociology
      • NCERT Solutions for Class 12 Psychology
  • Class 11
    • Class 11 Science
      • NCERT Solutions for Class 11 Maths
      • NCERT Solutions for Class 11 Physics
      • NCERT Solutions for Class 11 Chemistry
      • NCERT Solutions for Class 11 Biology
      • NCERT Solutions for Class 11 Economics
      • NCERT Solutions for Class 11 Computer Science (Python)
      • NCERT Solutions for Class 11 English
      • NCERT Solutions for Class 11 Hindi
    • Class 11 Commerce
      • NCERT Solutions for Class 11 Maths
      • NCERT Solutions for Class 11 Business Studies
      • NCERT Solutions for Class 11 Accountancy
      • NCERT Solutions for Class 11 Economics
      • NCERT Solutions for Class 11 Entrepreneurship
    • Class 11 Humanities
      • NCERT Solutions for Class 11 Psychology
      • NCERT Solutions for Class 11 Political Science
      • NCERT Solutions for Class 11 Economics
      • NCERT Solutions for Class 11 Indian Economic Development
  • Class 10
    • NCERT Solutions for Class 10 Maths
    • NCERT Solutions for Class 10 Science
    • NCERT Solutions for Class 10 Social Science
    • NCERT Solutions for Class 10 English
    • NCERT Solutions For Class 10 Hindi Sanchayan
    • NCERT Solutions For Class 10 Hindi Sparsh
    • NCERT Solutions For Class 10 Hindi Kshitiz
    • NCERT Solutions For Class 10 Hindi Kritika
    • NCERT Solutions for Class 10 Sanskrit
    • NCERT Solutions for Class 10 Foundation of Information Technology
  • Class 9
    • NCERT Solutions for Class 9 Maths
    • NCERT Solutions for Class 9 Science
    • NCERT Solutions for Class 9 Social Science
    • NCERT Solutions for Class 9 English
    • NCERT Solutions for Class 9 Hindi
    • NCERT Solutions for Class 9 Sanskrit
    • NCERT Solutions for Class 9 Foundation of IT
  • CBSE Sample Papers
    • Previous Year Question Papers
    • CBSE Topper Answer Sheet
    • CBSE Sample Papers for Class 12
    • CBSE Sample Papers for Class 11
    • CBSE Sample Papers for Class 10
    • Solved CBSE Sample Papers for Class 9 with Solutions 2024-2025
    • CBSE Sample Papers Class 8
    • CBSE Sample Papers Class 7
    • CBSE Sample Papers Class 6
  • Textbook Solutions
    • Lakhmir Singh
    • Lakhmir Singh Class 10 Physics
    • Lakhmir Singh Class 10 Chemistry
    • Lakhmir Singh Class 10 Biology
    • Lakhmir Singh Class 9 Physics
    • Lakhmir Singh Class 9 Chemistry
    • PS Verma and VK Agarwal Biology Class 9 Solutions
    • Lakhmir Singh Science Class 8 Solutions

Learn CBSE

NCERT Solutions for Class 6, 7, 8, 9, 10, 11 and 12

Probability Formulas

April 19, 2019 by Veerendra

Probability Formulas

Introduction to Probability

  • Sample–Space: The set of all possible outcomes of an experiment is called the Sample–Space(S).
  • Event: A subset of sample−space is called an Event.
  • Complement Of An Event A: The set of all out comes which are in S but not in A is called the Complement Of An Event A Denoted By \(\bar {A}\) Or Ac.
  • Compound Event: If A & B are two given events then A∩B is called Compound Event and is denoted by A∩B or AB or A & B.
  • Mutually Exclusive Events: Two events are said to be Mutually Exclusive Events (or disjoint or incompatible) if the occurence of one precludes (rules out) the simultaneous occurence of the other. If A & B are two mutually exclusive events then P (A & B) = 0.
  • Equally Likely Events: Events are said to be Equally Likely when each event is as likely to occur as any other event.
  • Exhaustive Events: Events A,B,C …….. L are said to be Exhaustive Events if no event outside this set can result as an outcome of an experiment. For example, if A & B are two events defined on a sample space S, then A & B are exhaustive ⇒ A∪B = S⇒ P (A∪B) = 1.
  • Classical Def. Of Probability: If n represents the total number of equally likely, mutually exclusive and exhaustive outcomes of an experiment and m of them are favourable to the happening of the event A, then the probability of happening of the event A is given by P(A) = m/n.
    Note:
    (1) 0 ≤ P(A) ≤ 1
    (2) P(A) + P( \(\bar {A}\) ) = 1, Where \(\bar {A}\) = Not A .
    (3) If x cases are favourable to \(\bar {A}\) & y cases are favourable to A then P(A) = \(\frac {x}{x+y}\) and P( \(\bar {A}\) ) = \(\frac {y}{x+y}\)
    We say that Odds In Favour Of A are x: y & odds against A are y : x

Comparative study of Equally likely , Mutually Exclusive and Exhaustive events.

Experiment Events E/L M/E Exhaustive
1. Throwing of a die A: throwing an odd face { 1, 3, 5}
B: throwing a composite face { 4, 6}
No Yes No
2. A ball is drawn from an urn containing 2W, 3R and 4G balls E1: getting a W ball
E2: getting a R ball
E3: getting a G ball
No Yes Yes
3. Throwing a pair of dice A: throwing a doublet { 11, 22, 33, 44, 55, 66}
B: throwing a total of 10 or more { 46, 64, 55, 56, 65, 66}
Yes No No
4. From a well shuffled pack of cards a card is drawn E1: getting a heart
E2: getting a spade
E3: getting a diamond
E4: getting a club
Yes Yes Yes
5. From a well shuffled pack of cards a card is drawn A = getting a heart
B = getting a face card
No No No

Results − 2
jee maths formulas 11
AUB = A+ B = A or B denotes occurence of at least A or B. For 2 events A & B : (See fig.1)

  • P(A∪B) = P(A) + P(B) − P(A∩B) = P(A. \(\bar {B}\) ) + P(\(\bar {A}\) .B) + P(A.B) = 1 − P( \(\bar {A}.\)\(\bar {B}\) )
  • Opposite of “atleast A or B” is Niether A nor B i.e. \(\bar {A + B}\) = 1-(A or B) = \(\bar {A}\) ∩ \(\bar {B}\)
    Note that P(A+B) + P( \(\overline{A} \cap \overline{B}\) ) = 1.
  • IfA & B are mutually exclusive then P(A∪B) = P(A) + P(B).
  • For any two events A & B, P(exactly one of A , B occurs)
    = P (A ∩ \(\bar {B}\)) + P (B ∩ \(\bar {A}\)) = P (A) + P (B) − 2P (A ∩ B)
    = P (A ∪ B) − P (A ∩ B) = P (Ac ∪ Bc ) − P(Ac ∩ Bc )
  • If A & B are any two events P(A∩B) = P(A).P(B/A) = P(B).P(A/B), Where P(B/A) means conditional
    probability of B given A & P(A/B) means conditional probability ofA given B. (This can be easily seen
    from the figure)
  • DE MORGAN’S LAW : − IfA & B are two subsets of a universal set U , then
    • (A∪B)c = Ac∩Bc &
    • (A∩B)c = Ac∪Bc
  • A ∪ (B∩C) = (A∪B) ∩ (A∪C) & A ∩ (B∪C) = (A∩B) ∪ (A∩C)

Result − 3
jee maths formulas 12
For any three events A,B and C we have (See Fig. 2)

  • P(A or B or C) = P(A) + P(B) + P(C) − P(A∩B) − P(B∩C)− P(C∩A) + P(A∩B∩C)
  • P (at least two of A,B,C occur) = P(B∩C) + P(C∩A) + P(A∩B) − 2P(A∩B∩C)
  • P(exactly two of A,B,C occur) = P(B∩C) + P(C∩A) + P(A∩B) − 3P(A∩B∩C)
  • P(exactly one of A,B,C occurs) = P(A) + P(B) + P(C) − 2P(B∩C) − 2P(C∩A) − 2P(A∩B)+3P(A∩B∩C)
    Note: If three events A, B and C are pair wise mutually exclusive then they must be mutually exclusive.
    i.e P(A∩B) = P(B∩C) = P(C∩A) = 0 ⇒ P(A∩B∩C) = 0. However the converse of this is not true.

Result − 4
Independent Events: Two events A & B are said to be independent if occurence or non occurence of one does not effect the probability of the occurence or non occurence of other.

  • If the occurence of one event affects the probability of the occurence of the other event then the events are said to be Dependent or Contingent. For two independent events A and B : P(A∩B) = P(A). P(B). Often this is taken as the definition of independent events.
  • Three events A , B & C are independent if & only if all the following conditions hold;
    P(A∩B) = P(A) . P(B) ; P(B∩C) = P(B) . P(C)
    P(C∩A) = P(C) . P(A) & P(A∩B∩C) = P(A) . P(B) . P(C)
    i.e. they must be pairwise as well as mutually independent.
    Similarly for n events A1, A2, A3, …… An to be independent, the number of these conditions is equal to nc2 + nc3 + ….. + ncn = 2n − n − 1.
  • The probability of getting exactly r success in n independent trials is given by P(r) = nCr pr qn-r
    where: p = probability of success in a single trial q = probability of failure in a single trial. note : p + q = 1
    Note: Independent events are not in general mutually exclusive & vice versa. Mutually exclusiveness can be used when the events are taken from the same experiment & independence can be used when the events are taken from different experiments.

Result − 5:
Baye’s Theorem Or Total Probability Theorem:

If an event A can occur only with one of the n mutually exclusive and exhaustive events B1, B2,… Bn & the probabilities P(A/B1), P(A/B2) ……. P(A/Bn) are known then,
jee maths formulas 13
\(P\left(B_{1} / A\right)=\frac{P\left(B_{i}\right) \cdot P\left(A / B_{i}\right)^{2}}{\sum_{i=1}^{n} P\left(B_{i}\right) \cdot P\left(A / B_{i}\right)}\)
Proof:
The events A occurs with one of the n mutually exclusive & exhaustive events B1, B2,B3,……..Bn; A = AB1 + AB2 + AB3 + ……. + ABn
\(\mathrm{P}(\mathrm{A})=\mathrm{P}\left(\mathrm{AB}_{1}\right)+\mathrm{P}\left(\mathrm{AB}_{2}\right)+\ldots \ldots+\mathrm{P}\left(\mathrm{AB}_{\mathrm{r}}\right)=\sum_{i=1}^{\mathrm{n}} \mathrm{P}\left(\mathrm{AB}_{\mathrm{i}}\right)\)
Note: A ≡ event what we have;
B1 ≡ event what we want ;
B2, B3, ….Bn are alternative event .
Now, P(ABi) = P(A) . P(Bi/A)
= P(Bi) . P(A/Bi)
\(P\left(B_{1} / A\right)=\frac{P\left(B_{1}\right) \cdot P\left(A / B_{i}\right)}{P(A)}=\frac{P\left(B_{1}\right) \cdot P\left(A / B_{i}\right)}{\sum_{i=1}^{n} P\left(A B_{i}\right)}\)
\(\mathrm{P}\left(\mathrm{B}_{\mathrm{i}} / \mathrm{A}\right)=\frac{\mathrm{P}\left(\mathrm{B}_{\mathrm{i}}\right) \cdot \mathrm{P}\left(\mathrm{A} / \mathrm{B}_{\mathrm{i}}\right)}{\sum \mathrm{P}\left(\mathrm{B}_{\mathrm{i}}\right) \cdot \mathrm{P}\left(\mathrm{A} / \mathrm{B}_{\mathrm{i}}\right)}\)

Result − 6
If p1 and p2 are the probabilities of speaking the truth of two indenpendent witnesses A and B thenP (their combined statement is true)
\(=\frac{\mathrm{p}_{1} \mathrm{p}_{2}}{\mathrm{p}_{1} \mathrm{p}_{2}+\left(1-\mathrm{p}_{1}\right)\left(1-\mathrm{p}_{2}\right)}.\)
In this case it has been assumed that we have no knowledge of the event except the statement made by A and B. However, if p is the probability of the happening of the event before their statement then P (their combined statement is true)
\(=\frac{\mathrm{p} \mathrm{p}_{1} \mathrm{p}_{2}}{\mathrm{pp}_{1} \mathrm{p}_{2}+(1-\mathrm{p})\left(1-\mathrm{p}_{1}\right)\left(1-\mathrm{p}_{2}\right)}\)
Here it has been assumed that the statement given by all the independent witnesses can be given in two ways only, so that if all the witnesses tell falsehoods they agree in telling the same falsehood. If this is not the case and c is the chance of their coincidence testimony then the Pr. that the statement is true = P p1 p2 Pr. that the statement is false = (1−p).c (1−p1)(1−p2)
However, chance of coincidence testimony is taken only if the joint statement is not contradicted by any witness.

Result − 7

  • A Probability Distribution spells out how a total probability of 1 is distributed over several values of a random variable.
  • Mean of any probability distribution of a random variable is given by
    \(\mu=\frac{\sum \mathrm{p}_{\mathrm{i}} \mathrm{x}_{\mathrm{i}}}{\sum \mathrm{p}_{\mathrm{i}}}=\sum \mathrm{p}_{\mathrm{i}} \mathrm{x}_{\mathrm{i}}\)  ( Since Σ pi = 1 )
  • Variance of a random variable is given by, σ² = ∑ ( xi − µ)² . pi
    σ² = ∑ pi x²i − µ² ( Note that SD = + \(\sqrt{\sigma^{2}}\) )
  • The probability distribution for a binomial variate ‘X’ is given by; P ( X = r ) = nCrpn qn-r  where all symbols have the same meaning as given in result 4. The recurrence formula
    \(\frac{\mathrm{P}(\mathrm{r}+1)}{\mathrm{P}(\mathrm{r})}=\frac{\mathrm{n}-\mathrm{r}}{\mathrm{r}+1} \cdot \frac{\mathrm{p}}{\mathrm{q}}\) is very helpful for quickly computing P(1) , P(2). P(3) etc. if P(0) is known.
  • Mean of BPD = np ; variance of BPD = npq.
  • If p represents a persons chance of success in any venture and ‘M’ the sum of money which he will receive in case of success, then his expectations or probable value = pM expectations = pM

Result − 8:
Geometrical Applications: The following statements are axiomatic:

  • If a point is taken at random on a given staright line AB, the chance that it falls on a particular segment PQ of the line is PQ/AB .
  • If a point is taken at random on the area S which includes an area σ, the chance that the point falls on σ is σ/S .

Filed Under: CBSE Tagged With: basic probability formulas, equation for probability, formula for probability, how do you find probability, introduction to probability, probability equation, probability equations, probability formula, probability formulas, probability of a and b formula, sample space formula

LearnCBSE.in Student Education Loan
  • Student Nutrition - How Does This Effect Studies
  • Words by Length
  • NEET MCQ
  • Factoring Calculator
  • Rational Numbers
  • CGPA Calculator
  • TOP Universities in India
  • TOP Engineering Colleges in India
  • TOP Pharmacy Colleges in India
  • Coding for Kids
  • Math Riddles for Kids with Answers
  • General Knowledge for Kids
  • General Knowledge
  • Scholarships for Students
  • NSP - National Scholarip Portal
  • Class 12 Maths NCERT Solutions
  • Class 11 Maths NCERT Solutions
  • NCERT Solutions for Class 10 Maths
  • NCERT Solutions for Class 9 Maths
  • NCERT Solutions for Class 8 Maths
  • NCERT Solutions for Class 7 Maths
  • NCERT Solutions for Class 6 Maths
  • NCERT Solutions for Class 6 Science
  • NCERT Solutions for Class 7 Science
  • NCERT Solutions for Class 8 Science
  • NCERT Solutions for Class 9 Science
  • NCERT Solutions for Class 10 Science
  • NCERT Solutions for Class 11 Physics
  • NCERT Solutions for Class 11 Chemistry
  • NCERT Solutions for Class 12 Physics
  • NCERT Solutions for Class 12 Chemistry
  • NCERT Solutions for Class 10 Science Chapter 1
  • NCERT Solutions for Class 10 Science Chapter 2
  • Metals and Nonmetals Class 10
  • carbon and its compounds class 10
  • Periodic Classification of Elements Class 10
  • Life Process Class 10
  • NCERT Solutions for Class 10 Science Chapter 7
  • NCERT Solutions for Class 10 Science Chapter 8
  • NCERT Solutions for Class 10 Science Chapter 9
  • NCERT Solutions for Class 10 Science Chapter 10
  • NCERT Solutions for Class 10 Science Chapter 11
  • NCERT Solutions for Class 10 Science Chapter 12
  • NCERT Solutions for Class 10 Science Chapter 13
  • NCERT Solutions for Class 10 Science Chapter 14
  • NCERT Solutions for Class 10 Science Chapter 15
  • NCERT Solutions for Class 10 Science Chapter 16

Free Resources

RD Sharma Class 12 Solutions RD Sharma Class 11
RD Sharma Class 10 RD Sharma Class 9
RD Sharma Class 8 RD Sharma Class 7
CBSE Previous Year Question Papers Class 12 CBSE Previous Year Question Papers Class 10
NCERT Books Maths Formulas
CBSE Sample Papers Vedic Maths
NCERT Library

NCERT Solutions

NCERT Solutions for Class 10
NCERT Solutions for Class 9
NCERT Solutions for Class 8
NCERT Solutions for Class 7
NCERT Solutions for Class 6
NCERT Solutions for Class 5
NCERT Solutions for Class 4
NCERT Solutions for Class 3
NCERT Solutions for Class 2
NCERT Solutions for Class 1

Quick Resources

English Grammar Hindi Grammar
Textbook Solutions Maths NCERT Solutions
Science NCERT Solutions Social Science NCERT Solutions
English Solutions Hindi NCERT Solutions
NCERT Exemplar Problems Engineering Entrance Exams
Like us on Facebook Follow us on Twitter
Watch Youtube Videos NCERT Solutions App